Bachelor of Science in Artificial Intelligence and Machine Learning

Provide a strong foundation in AI/ML theory: Enable students to acquire broad and in-depth knowledge of artificial intelligence and machine learning principles, including foundational mathematics, algorithms, and domain-specific knowledge, so they understand both classical approaches and state-of-the-art techniques in the field. Develop advanced technical skills: Equip students with proficient technical abilities to design, build, and deploy AI systems. This includes programming competency, data analysis skills, experience with AI/ML frameworks and tools, software engineering practices for AI, and exposure to technologies like cloud computing and MLOps for model deployment. Foster analytical and problem-solving capabilities: Cultivate students’ ability to think critically and solve complex problems using AI techniques. They will learn to identify appropriate AI methods for a given problem, analyze data and model performance rigorously, and innovate in applying computational solutions to real-world challenges. Instill ethical and professional values: Ensure students develop a strong sense of ethics, responsibility, and societal awareness in AI practice. The programme emphasizes understanding the ethical implications of AI (such as fairness, accountability, and privacy) and encourages students to be conscientious and professional when collaborating on projects or making decisions as AI practitioners. Enhance collaborative and communication skills: Train students to work effectively in teams and communicate their ideas clearly. Students will engage in group projects and presentations to build teamwork, leadership, and communication skills, enabling them to explain complex AI concepts to both technical colleagues and non-specialist stakeholders. Prepare graduates for careers or further study: Ready students for immediate employment in AI/ML roles or for postgraduate education. By graduation, students will have a portfolio of project work and practical experience (including a capstone project/internship) that demonstrates their capabilities, positioning them to take on professional positions such as AI engineer, data scientist, machine learning specialist, or to pursue advanced research and studies in the field.

AI Systems Architect, Deep Learning Engineer, Machine Learning Engineer